Metrics in Healthcare are pieces of information upon which medical practitioners and researchers can base measurements. For examples, doctors can measure whether patients are taking a particular medication, or if they are following an exercise program or even the last time they visited their primary care physician.
So put simply, Metrics in Healthcare are facts about the patients in the cohorts that can be changed, and to which a value can be assigned. Tracking those values will tell you whether the quality improvements that have instituted are delivering the desired outcomes for those cohorts. And this is the defining relationship between healthcare metrics and quality improvements.
One of the common challenges in a quality improvement project is ensuring you can get the information you need. In the case of clinical information, while it is stored in the Electronic Health Record (EHR), it may not be entered there consistently. In other words, while there may be a field with a drop-down to include the information that will contribute to your metrics, that doesn’t guarantee that the information is there. It may have been entered in the free text notes or five other places instead. If that is the case, your clinical program team will need to determine where the best place to capture that information is and how to gain compliance among the clinicians you are working with to ensure they enter data in the same place consistently.
Now that the area for improvement is defined and the team is in place, it’s time to build the cohort and start defining the clinical metrics. If you have an electronic data warehouse, you should be able to build the cohort quickly by expanding on the parameters used for the KPA, refining it as-needed and running a query. Without an electronic data warehouse or an analytics application that can delve into your electronic health records, you are looking at a long, tedious manual process.
Then it’s time to determine what to measure. There are several ways to make that determination. Many clinical metrics are driven by government regulations. These are things you have to do, so they make a good starting point when you’re defining your clinical metrics. You’ll want to review evidence-based literature as well to see what the best practices for that area are and whether you’re following them.
You should also gather all your stakeholders together and ask them. Based on their experience, they will have many ideas for solving quality issues, and their buy-in is important. The downside of all this investigation is once the ideas start flowing, you often end up with too many metrics. At this point, you have two options.
- Identify a goal for quality improvement and put all the ideas into a “bank” to draw on when you decide to move forward. If your goal is to increase the number of new mothers who breastfeed you may consider dozens of potential measurements such as the mother’s age, if it is her first child, who her obstetrician is, whether she breastfed before, her education level, etc. At some point, however, you will need to decide which of these elements to focus on, or the program will become too unwieldy.
- The second option—and the option that’s highly recommended—is to start with a smaller group of clinical metrics based on an aim statement. Aim statements are powerful because they focus on a specific improvement in a specific population, and provide a timeframe to accomplish it. They give quality improvement teams a sense of direction and help them identify the steps that need to be taken to accomplish those goals. With the aim statement defined, it is easy to determine which metrics support it. The workgroup can then use this information to determine the process changes and evidence-based interventions that will be required to remove barriers and achieve the desired quality outcomes. It can also help identify what information to examine to determine whether the new processes are being followed and make corrections to ensure the quality improvement project’s standards are being followed.